The present disclosure relates generally to data storage, and, in particular, to a multi-resolution storage scheme for historical data.
Since society is increasingly relying on computer systems for smooth and efficient operation, the demand for computer systems to run without interruption for long intervals of time has correspondingly grown. A monitoring tool may be used to monitor a computer system's performance and indicate whether the computer system's performance has or will deteriorate over time. Such a monitoring tool can provide an early warning of a developing problem before the monitored computer system reaches a point of severely degraded performance or failure. Using information provided by the monitoring tool, system parameters can be adjusted to maintain and/or improve performance of the monitored computer system. For an early warning system to properly predict problems, a significant volume of historical data is generally required to make statistically significant predictions. Therefore, historical data must be collected over long intervals of time to enable accurate predictions.
The collection of a large volume of data can lead to potential storage issues, such as a high total cost of storage. Data compression can reduce the amount of space needed to store data, but the accuracy of the compressed data is typically degraded, as granularity is diminished during the compression process. In monitoring and prediction systems, it is important that recent data be more precise as compared to older data, because the recent data is more significant for prediction purposes. Therefore, to increase storage efficiency, it would be beneficial to develop a flexible compression technique, adjusting for factors such as storage and error tolerance constraints through non-uniform compression ratios. Accordingly, there is a need in the art for a multi-resolution storage scheme for historical data.